Transmit Power Allocation for BER Performance Improvement in Multicarrier Systems
|
|
- Joel Holland
- 6 years ago
- Views:
Transcription
1 Transmit Power Allocation for Performance Improvement in Systems Chang Soon Par O and wang Bo (Ed) Lee School of Electrical Engineering and Computer Science, Seoul National University parcs@mobile.snu.ac.r, lee@snu.ac.r Abstract In a wireless multicarrier system, transmit power allocation over different subchannels is an effective means to improve the performance. In this paper, the optimal transmit power allocation scheme is developed to improve the bit error rate () performance in a multicarrier system with diversity reception. A simple suboptimal scheme is also derived from the optimal one, and an asymptotic case is discussed. Numerical results show that the optimal and suboptimal power allocation schemes significantly outperform the equal power allocation scheme. The effects of the modulation level, the number of receiving antennas, and the number of subchannels on the performance are also investigated. I. INTRODUCTION communication system is promising for future wideband wireless communications, and recently the system is being applied to several fixed and mobile radio systems, such as digital audio and video broadcasting, and wireless LAN [], []. In a multicarrier system, a wideband channel is divided into multiple narrowband subchannels using orthogonal subcarriers, and multiple data streams are transmitted in parallel through these subchannels. In a multicarrier system, it is natural to allocate equal transmit power to multiple subchannels, when the channel state information is not available at the transmitter. When the channel state information is available at the transmitter, however, effective transmit power allocation may improve error rate performance or increase the capacity. Transmit power allocation based on the water-filling solution has been studied in [3] and [4], and it has been combined with adaptive modulation to maximize the capacity [5], [6]. These schemes of increasing capacity may be suitable for variable rate services such as and web browsing. On the contrary, delay-sensitive services such as voice or video are usually provided at a fixed rate. In these applicases, it is desirable to design a transmit power allocation scheme that improves error rate performance for a given rate. In this paper, we develop the optimal transmit power allocation scheme to improve bit error rate () performance in a multicarrier system with receive antenna diversity. Receive antenna diversity is used to mitigate the effects of fading [], []. Based on the optimal scheme, a computationally efficient suboptimal scheme is also derived. Furthermore, it is shown that an asymptotic case of the suboptimal scheme corresponds to the equal signalto-noise ratio (SNR) scheme, by which the received SNR becomes the same for all subchannels. The performance of the proposed power allocation schemes is evaluated, and compared with that of the equal power allocation scheme. The effects of the modulation level, the number of receiving antennas, and the number of subchannels on the performance are also investigated. Numerical results show that the use of the optimal or suboptimal power allocation scheme significantly improves the performance of a multicarrier system. The equal SNR scheme is found to perform well in the presence of large number of receiving antennas. The remainder of this paper is organized as follows. Section II describes the system and channel models. In Section III, the optimal transmit power allocation scheme is derived, and a simple suboptimal scheme is derived from the optimal one. An asymptotic case of the suboptimal scheme is also investigated in Section III. Numerical results are presented in Section IV, and conclusions are drawn in Section V. II. SYSTEM AND CHANNEL MODELS A wireless multicarrier system considered in this paper is depicted in Fig.. An input data stream is divided into parallel substreams through a serial-to-parallel converter. The transmit power p is assigned to the th substream ( =,,, ). In the multicarrier modulator, the substreams are modulated on orthogonal subcarriers to form a transmit signal. The receiver is equipped with N antennas, from which N replicas of the transmit signal for each subcarrier are received. It is assumed that the signals received from different antennas experience independent, slowly varying, frequency-nonselective Rayleigh fading. The output of a multicarrier for the th subcarrier at the nth receive antenna may be expressed as y, n = p h, nd + n, n, =,,,, n =,,, N () where h,n denotes the multiplicative fading coefficient for
2 the th subcarrier at the nth antenna, and they are assumed to be independent and identically distributed (i.i.d.) complex Gaussian random variables with zero mean and unit variance. n,n s represent the additive white Gaussian noise (AWGN), and they are assumed to be i.i.d. complex Gaussian random variables with zero mean and variance of. d is the encoded data symbol with unit average power, and p is the transmit power for the th subcarrier with the total power constraint given as p = P, p () = where P denotes the average transmit power per subcarrier, when the total transmit power is equally distributed into the subcarriers. As shown in Fig., signals received from N antennas are combined for each subcarrier to achieve antenna gain and diversity gain. It is assumed that the maximal ratio combining () is employed to maximize the SNR []. The transmitted symbol on each subcarrier is estimated based on the output of each. After, the SNR for the th subcarrier may be calculated as γ = α p (3) where N n =, n α h σ is the ratio of the combined channel gain for the th subchannel to the noise power, representing the overall channel state for the th subchannel. The channel states ( =,,, ) are required to determine the transmit power p ( =,,, ), and they are assumed to be perfectly nown to the transmitter. These channel states can be obtained by feedbac from the receiver in a frequency division duplex (FDD) system, or can be estimated at the transmitter in a time division duplex (TDD) system. III. TRANSMIT POWER ALLOCATION In this section, several transmit power allocation schemes are described. The equal power allocation scheme is briefly discussed in Section III-A, and power allocation scheme that is optimal in terms of the is developed in Section III-B. A suboptimal scheme is derived as a simplified version of the optimal scheme in Section III-C, and the equal SNR scheme is discussed as an asymptotic case of the suboptimal scheme in Section III-D. A. Equal Power Allocation When the channel state information is not available at the transmitter, it is natural to allocate equal transmit power to subcarriers. This scheme is referred to as the equal power allocation scheme. In this scheme, the transmit power for each subcarrier is P in (), and the SNR γ for the th subcarrier is α P. When the channel state information is available at the transmitter, the total transmit power may be allocated in a more effective way to achieve better performance, as described in the following subsections. B. Power Allocation To derive the optimal power allocation scheme, we first express the overall as a function of the transmit power of subcarriers, { p =,,, }, and then find { p } that minimizes the overall. The for the th subcarrier is generally a function of the SNR γ, and thus the Pb ( e α ) for a given channel state α may be expressed as P ( e α ) = f α p, =,,, (4) b where f ( ) is a function determined by a specific modulation scheme. Since data streams are transmitted over independent subchannels, the overall for given channel states of { α } can be calculated as an arithmetic mean of P ( e α ) in (4): b P ( e α, α,, α ) = f α p. (5) b = Note that the average becomes minimal when the in (5) is minimized for each given channel state. To find the optimal {p } that minimizes (5), we use the Lagrange multiplier method with the total power constraint in (). The Lagrangian function may be expressed as J ( p, p,, p ) = f ( α p ) + λ p P (6) = = where λ denotes the Lagrange multiplier. By differentiating (6) with respect to p and setting it to zero, we obtain a set of equations as d f ( α p ) + λ =, =,,,. (7) dp Solving + simultaneous equations in () and (7), we can calculate the optimal set of the transmit power {p }. As mentioned above, the function in (4) is a function determined by a specific modulation scheme. For differential phase-shift eying (DPS) scheme, for example, the function may be expressed as an exponential function [] and a closed-form solution of () and (7) may be easily found. For M-ary phase-shift eying (PS) or M-ary quadrature amplitude modulation (QAM) scheme, however, the exact or approximate function may be expressed as a Q-function [] and it may be difficult to find a closed-form solution. In this case, an adaptive method such as the steepest descent algorithm [7] may be employed to find a solution in an iterative manner as follows. Step ) Initialization: Set an iteration number i =, a step size µ() = µ and an arbitrary initial power set {p ()} satisfying (). Step ) Updating the power set: For =,,,, update the transmit power p (i) as p ( i + ) = p µ J ( p, p,, p ) p (8) d = p µ f ( α p ) + λ dp where λ(i) is determined from the power
3 constraint in () and is updated as d λ = f ( p ) α. (9) dp = Step 3) Adjusting the step size in case of negative power: If all components of the calculated power set in Step are non-negative, then go to Step 4 with µ(i+) = µ. Otherwise, adjust the step size µ(i) so that the negative components can be non-negative, and return to Step. Step 4) Repetition or termination: If more adaptations are required for convergence, increase i by one and go to Step. Otherwise, terminate the adaptive procedure. Note that the adaptive solution described above converges to the global optimum solution for the convex function [8], if the number of iterations is sufficiently large and the step size is sufficiently small. The Q-function, which is the exact or approximate function for M-ary PS or M-ary QAM modulation scheme, is a convex function. C. Power Allocation In case that a closed-form solution cannot be found, an adaptive method may be used to find the optimal solution, as described in the previous subsection. However, it generally taes a lot of iterations for an adaptive solution to be close to the optimal one. A simpler approach is to find an approximate closed-form solution using a simple approximation of the rather than the exact expression. Based on this approach, in this subsection, we derive a closed-form solution for M-ary square (M = 4 m, m =,, ) QAM schemes. The derivation procedure may easily be applied to other modulation schemes with modifications for approximate functions. For an M- ary square QAM, the function in (4) may be approximated using an upper bound as [9], [] a b f ( α p ) aq( bα p ) exp α p () where ( π ) exp( ) x Q x t dt denotes the Q- ( M ) function, a =, and b = 3 ( M ). By M log M substituting the upper bound in () into the function of (7), we can find a closed-form solution of + simultaneous equations in () and (7). Some components of the calculated power set may be negative. In this case, we can apply the uhn-tucer conditions [8], from which the negative components of {p } are set to zero and the remaining components are recalculated until all components become non-negative. Consequently, the solution is given as λ α ( b)( α ) ln ( α ), α exp( bλ / ) p =, α < exp( bλ / ) () 4λ where λ ln. To satisfy the power constraint b ab in (), λ is calculated as P + ( b)( α ) ln ( α ) S λ = () α ( ) S where S { α exp( bλ / ) } =. From (), it can be seen that no transmit power is allocated to the th subcarrier if the channel state is smaller than exp( bλ / ). D. Power Allocation In this subsection, the equal SNR power allocation scheme is derived from an asymptotic solution of (). From (), it can be shown that p approaches λ as goes to infinity for all. Thus, the power allocation and the corresponding SNR may be calculated as P p = λ α =, (3) α α = ( α ) = P γ = λ =, =,,,. (4) Equation (4) indicates that the suboptimal scheme of () behaves lie the equal SNR scheme, when is sufficiently large for all. In other words, the received SNR becomes the same for all subchannels, when all the subchannels are in sufficiently good conditions. This equal SNR scheme allocates transmit power inversely proportional to the channel state, allocating the more transmit power to the more attenuated subchannel. Hence, as compared to the equal power scheme, the equal SNR scheme increases the received SNR of relatively worse subchannels, while decreases that of relatively better subchannels. IV. NUMERICAL RESULTS In this section, the performance of the power allocation schemes described in Section III are evaluated and compared with one another. An M-ary square QAM modulation is assumed to be employed for each subcarrier, and adaptive procedure in Section III-B is used to calculate the allocated power for the optimal scheme with sufficient iterations. Equations () and () are used to determine the allocated power for the suboptimal scheme, and equation (3) is used for the equal SNR scheme. The average SNR is defined to be P / σ. The average for each transmit power allocation scheme is calculated by averaging the in (5) for sufficient number of randomly generated channel states { α =,,, }. The characteristics of power allocation schemes are depicted in Fig., which shows the power calculated from three power allocation schemes for given values of, when the number of subcarriers =, modulation level M = 4, and P =. Note that larger value of corresponds to lower attenuation of the combined channel for the th subcarrier. The optimal power allocation
4 scheme is observed to assign the more transmit power to the less attenuated subchannel, when is smaller than an intermediate value,.6 in Fig.. For greater than.6, on the contrary, the more transmit power is assigned to the more attenuated subchannel. Hence, the optimal power allocation may be viewed as a combination of inverse water-filling and water-filling strategies. The trends of the suboptimal power allocation scheme are shown to be similar to that of the optimal power allocation scheme, except that the power corresponding to some highly attenuated subchannels is forced to zero. As expected, the equal SNR scheme allocates the more transmit power to the more attenuated subchannel. Fig. 3 compares the performance of the transmit power allocation schemes for various modulation level M, when = 5 and N =. As expected, the optimal power allocation scheme provides the best performance for all cases. In the case of QPS modulation (M = 4), for example, the SNR gain of the optimal scheme is about 3. db over the equal power scheme, and. db over the equal SNR scheme at a of -3. It is noticeable that the performance of the optimal and suboptimal schemes is almost indistinguishable at high SNR range, especially for low modulation levels. At low SNR range, however, the curve of the suboptimal scheme significantly deviates from that of the optimal scheme, since the difference between the exact and approximate becomes significant with SNR decreasing. The performance improvement of the optimal and suboptimal schemes over the other schemes is found to be a little larger for lower modulation level. The equal SNR scheme outperforms the equal power scheme at high SNR range, while the trend is reversed at low SNR range. This may be a consequence of two conflicting effects of the equal SNR scheme compared to the equal power scheme. As mentioned in Section III-D, the equal SNR scheme increases the received SNR of relatively worse subchannels, while decreases that of relatively better subchannels. Numerical results in Fig. 3 indicates that the effect of the former on the overall performance is more significant at high SNR range, while that of the latter is more significant at low SNR range. The effects of the number of receiving antennas N on the performance are shown in Fig. 4, when M = 4 and = 4. As shown in Fig. 3, the optimal and suboptimal schemes significantly outperform the equal power scheme, for any value of N. We can observe that the equal SNR scheme also outperforms the equal power scheme, unless the SNR is very low or the number of receiving antennas is small. Furthermore, the performance of the equal SNR scheme is found to approach that of the optimal scheme, as N increases. This implies that increased diversity effects resulting from more receiving antennas provide higher probability of the combined channels being in sufficiently good condition for all subcarriers. Hence, the use of equal SNR scheme may be desirable, when the number of receiving antennas is sufficiently large. Fig. 5 shows the effects of the number of subcarriers on the performance, when M = 4 and N =. Note that the performance of the equal power scheme is irrespective of. The SNR gains of the optimal and equal SNR schemes over the equal power scheme are found to increase with increasing. Note that greater also maes the for the proposed power allocation schemes decline more rapidly with SNR increasing. This phenomenon indicates that an increase in the number of subchannels can provide additional diversity effects through the use of proposed power allocation schemes. V. CONCLUSIONS In this paper, we have developed the optimal transmit power allocation scheme that improves the performance in a wireless multicarrier system with diversity reception. A computationally efficient suboptimal scheme has also been derived for M-ary QAM, and the equal SNR scheme has been shown to be an asymptotic case of the suboptimal scheme. Numerical results have shown that the optimal power allocation scheme provides about 3. db of SNR gain over the equal power scheme at a of -3 for 5 subchannels, receiving antennas, and QPS modulation. The performance improvement of the optimal scheme has been found to increase, as the number of subchannels increases. The suboptimal scheme performs as well as the optimal scheme at high SNR range. It has also been found that the performance of the equal SNR scheme approaches that of the optimal scheme, as the number of receiving antennas increases. REFERENCES [] J. G. Proais, Digital Communications. New Yor: McGraw-Hill, 995. [] A. A. Hutter, J. S. Hammerschmidt, E. Carvalho, and J. M. Cioffi, Receive diversity for mobile OFDM systems, in Proc. IEEE WCNC, Chicago, USA, Sept., pp [3] T. M. Cover and J. A. Thomas, Elements of Information Theory. New Yor: Wiley, 99. [4] J. Jang,. B. Lee, and Y.-H. Lee, Frequency-time domain transmit power adaptation for a multicarrier system in fading channels, in Proc. PI, San Diego, USA, Sept.-Oct., pp. D D3. [5] A. J. Goldsmith and S.-G. Chua, Variable-rate variablepower MQAM for fading channels, IEEE Trans. Commun., vol. 45, pp. 8-3, Oct [6] S. T. Chung and A. J. Goldsmith, Adaptive multicarrier modulation for wireless systems, in Proc. 34th Asilomar Conf. Signals, Syst., Comput.,, vol., pp [7] B. Widrow and S. D. Stearns, Adaptive Signal Processing. Englewood Cliffs, NJ: Prentice-Hall, 985. [8] D. G. Luenberger, Introduction to Linear and Nonlinear Programming. Reading, MA: Addison-Wesley, 973. [9] M.. Simon, S. M. Hinedi, and W. C. Lindsey, Digital Communication Techniques. Englewood Cliffs, NJ: Prentice-Hall, 995. [] J. M. Wozencraft and I. M. Jacobs, Principles of Communication Engineering. New Yor: Wiley, 965.
5 FIGURES d Transmitter Power Allocation Channel # y, y, y, Receiver ^d Input data Serial-toparallel converter d d p p p modulator # #N y, y, y, y,n y,n y,n ^ d ^ d Paralleltoserial converter Output data Fig.. communication system with receive antenna diversity N = N = 4 - p 3-3 N = 3-4 Equal Power - α Fig.. Power allocation for M = 4, =, and P = Fig. 4. Effects of the number of receiving antennas N on the performance of power allocation schemes, when M = 4 and = 4. - M = 4 M = 6 M = Equal Power -3-4 Equal Power (=3,5,7) (=3) (=3) (=5) (=5) (=7) (=7) Fig. 3. performance comparisons of power allocation schemes for = 5 and N = Fig. 5. Effects of the number of subcarriers on the performance of power allocation schemes, when M = 4 and N =.
MULTICARRIER communication systems are promising
1658 IEEE TRANSACTIONS ON COMMUNICATIONS, VOL. 52, NO. 10, OCTOBER 2004 Transmit Power Allocation for BER Performance Improvement in Multicarrier Systems Chang Soon Park, Student Member, IEEE, and Kwang
More informationDynamic Subchannel and Bit Allocation in Multiuser OFDM with a Priority User
Dynamic Subchannel and Bit Allocation in Multiuser OFDM with a Priority User Changho Suh, Yunok Cho, and Seokhyun Yoon Samsung Electronics Co., Ltd, P.O.BOX 105, Suwon, S. Korea. email: becal.suh@samsung.com,
More informationDegrees of Freedom in Adaptive Modulation: A Unified View
Degrees of Freedom in Adaptive Modulation: A Unified View Seong Taek Chung and Andrea Goldsmith Stanford University Wireless System Laboratory David Packard Building Stanford, CA, U.S.A. taek,andrea @systems.stanford.edu
More informationPERFORMANCE ANALYSIS OF DIFFERENT M-ARY MODULATION TECHNIQUES IN FADING CHANNELS USING DIFFERENT DIVERSITY
PERFORMANCE ANALYSIS OF DIFFERENT M-ARY MODULATION TECHNIQUES IN FADING CHANNELS USING DIFFERENT DIVERSITY 1 MOHAMMAD RIAZ AHMED, 1 MD.RUMEN AHMED, 1 MD.RUHUL AMIN ROBIN, 1 MD.ASADUZZAMAN, 2 MD.MAHBUB
More informationA LOW COMPLEXITY SCHEDULING FOR DOWNLINK OF OFDMA SYSTEM WITH PROPORTIONAL RESOURCE ALLOCATION
A LOW COMPLEXITY SCHEDULING FOR DOWNLINK OF OFDMA SYSTEM WITH PROPORTIONAL RESOURCE ALLOCATION 1 ROOPASHREE, 2 SHRIVIDHYA G Dept of Electronics & Communication, NMAMIT, Nitte, India Email: rupsknown2u@gmailcom,
More informationTransmit Power Adaptation for Multiuser OFDM Systems
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, VOL. 21, NO. 2, FEBRUARY 2003 171 Transmit Power Adaptation Multiuser OFDM Systems Jiho Jang, Student Member, IEEE, Kwang Bok Lee, Member, IEEE Abstract
More informationCombined Transmitter Diversity and Multi-Level Modulation Techniques
SETIT 2005 3rd International Conference: Sciences of Electronic, Technologies of Information and Telecommunications March 27 3, 2005 TUNISIA Combined Transmitter Diversity and Multi-Level Modulation Techniques
More informationCHAPTER 3 ADAPTIVE MODULATION TECHNIQUE WITH CFO CORRECTION FOR OFDM SYSTEMS
44 CHAPTER 3 ADAPTIVE MODULATION TECHNIQUE WITH CFO CORRECTION FOR OFDM SYSTEMS 3.1 INTRODUCTION A unique feature of the OFDM communication scheme is that, due to the IFFT at the transmitter and the FFT
More informationStudy of Turbo Coded OFDM over Fading Channel
International Journal of Engineering Research and Development e-issn: 2278-067X, p-issn: 2278-800X, www.ijerd.com Volume 3, Issue 2 (August 2012), PP. 54-58 Study of Turbo Coded OFDM over Fading Channel
More informationBeamforming with Imperfect CSI
This full text paper was peer reviewed at the direction of IEEE Communications Society subject matter experts for publication in the WCNC 007 proceedings Beamforming with Imperfect CSI Ye (Geoffrey) Li
More informationA Novel Spread Spectrum System using MC-DCSK
A Novel Spread Spectrum System using MC-DCSK Remya R.V. P.G. scholar Dept. of ECE Travancore Engineering College Kollam, Kerala,India Abstract A new spread spectrum technique using Multi- Carrier Differential
More informationDynamic Subcarrier, Bit and Power Allocation in OFDMA-Based Relay Networks
Dynamic Subcarrier, Bit and Power Allocation in OFDMA-Based Relay Networs Christian Müller*, Anja Klein*, Fran Wegner**, Martin Kuipers**, Bernhard Raaf** *Communications Engineering Lab, Technische Universität
More informationCognitive Radio Transmission Based on Chip-level Space Time Block Coded MC-DS-CDMA over Fast-Fading Channel
Journal of Scientific & Industrial Research Vol. 73, July 2014, pp. 443-447 Cognitive Radio Transmission Based on Chip-level Space Time Block Coded MC-DS-CDMA over Fast-Fading Channel S. Mohandass * and
More informationRate and Power Adaptation in OFDM with Quantized Feedback
Rate and Power Adaptation in OFDM with Quantized Feedback A. P. Dileep Department of Electrical Engineering Indian Institute of Technology Madras Chennai ees@ee.iitm.ac.in Srikrishna Bhashyam Department
More informationMargin Adaptive Resource Allocation for Multi user OFDM Systems by Particle Swarm Optimization and Differential Evolution
Margin Adaptive Resource Allocation for Multi user OFDM Systems by Particle Swarm Optimization and Differential Evolution Imran Ahmed, Sonia Sadeque, and Suraiya Pervin Northern University Bangladesh,
More informationPower Allocation Tradeoffs in Multicarrier Authentication Systems
Power Allocation Tradeoffs in Multicarrier Authentication Systems Paul L. Yu, John S. Baras, and Brian M. Sadler Abstract Physical layer authentication techniques exploit signal characteristics to identify
More informationAdaptive Resource Allocation in Multiuser OFDM Systems with Proportional Rate Constraints
TO APPEAR IN IEEE TRANS. ON WIRELESS COMMUNICATIONS 1 Adaptive Resource Allocation in Multiuser OFDM Systems with Proportional Rate Constraints Zukang Shen, Student Member, IEEE, Jeffrey G. Andrews, Member,
More informationPerformance Evaluation of different α value for OFDM System
Performance Evaluation of different α value for OFDM System Dr. K.Elangovan Dept. of Computer Science & Engineering Bharathidasan University richirappalli Abstract: Orthogonal Frequency Division Multiplexing
More informationResource Allocation for Multipoint-to-Multipoint Orthogonal Multicarrier Division Duplexing
Resource Allocation for Multipoint-to-Multipoint Orthogonal Multicarrier Division Duplexing Poramate Tarasa and Hlaing Minn Institute for Infocomm Research, Agency for Science, Technology and Research
More informationCOMPARISON OF CHANNEL ESTIMATION AND EQUALIZATION TECHNIQUES FOR OFDM SYSTEMS
COMPARISON OF CHANNEL ESTIMATION AND EQUALIZATION TECHNIQUES FOR OFDM SYSTEMS Sanjana T and Suma M N Department of Electronics and communication, BMS College of Engineering, Bangalore, India ABSTRACT In
More informationAn Equalization Technique for Orthogonal Frequency-Division Multiplexing Systems in Time-Variant Multipath Channels
IEEE TRANSACTIONS ON COMMUNICATIONS, VOL 47, NO 1, JANUARY 1999 27 An Equalization Technique for Orthogonal Frequency-Division Multiplexing Systems in Time-Variant Multipath Channels Won Gi Jeon, Student
More informationThe Impact of Imperfect One Bit Per Subcarrier Channel State Information Feedback on Adaptive OFDM Wireless Communication Systems
The Impact of Imperfect One Bit Per Subcarrier Channel State Information Feedback on Adaptive OFDM Wireless Communication Systems Yue Rong Sergiy A. Vorobyov Dept. of Communication Systems University of
More informationA Linear-Complexity Resource Allocation Method for Heterogeneous Multiuser OFDM Downlink
A Linear-Complexity Resource Allocation Method for Heterogeneous Multiuser OFDM Downlin Chunhui Liu, Ane Schmein and Rudolf Mathar Institute for Theoretical Information Technology, UMIC Research Centre,
More informationA Utility-Approached Radio Resource Allocation Algorithm for Downlink in OFDMA Cellular Systems
A Utility-Approached Radio Resource Allocation Algorithm for Downlin in OFDMA Cellular Systems Lue T. H. Lee Chung-Ju Chang Yih-Shen Chen and Scott Shen Department of Communication Engineering National
More informationLecture 3: Wireless Physical Layer: Modulation Techniques. Mythili Vutukuru CS 653 Spring 2014 Jan 13, Monday
Lecture 3: Wireless Physical Layer: Modulation Techniques Mythili Vutukuru CS 653 Spring 2014 Jan 13, Monday Modulation We saw a simple example of amplitude modulation in the last lecture Modulation how
More informationWireless Communication: Concepts, Techniques, and Models. Hongwei Zhang
Wireless Communication: Concepts, Techniques, and Models Hongwei Zhang http://www.cs.wayne.edu/~hzhang Outline Digital communication over radio channels Channel capacity MIMO: diversity and parallel channels
More information3432 IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. 53, NO. 10, OCTOBER 2007
3432 IEEE TRANSACTIONS ON INFORMATION THEORY, VOL 53, NO 10, OCTOBER 2007 Resource Allocation for Wireless Fading Relay Channels: Max-Min Solution Yingbin Liang, Member, IEEE, Venugopal V Veeravalli, Fellow,
More informationSimplified Levenberg-Marquardt Algorithm based PAPR Reduction for OFDM System with Neural Network
Simplified Levenberg-Marquardt Algorithm based PAPR Reduction for OFDM System with Neural Network Rahul V R M Tech Communication Department of Electronics and Communication BCCaarmel Engineering College,
More informationOFDM Transmission Corrupted by Impulsive Noise
OFDM Transmission Corrupted by Impulsive Noise Jiirgen Haring, Han Vinck University of Essen Institute for Experimental Mathematics Ellernstr. 29 45326 Essen, Germany,. e-mail: haering@exp-math.uni-essen.de
More informationPeak-to-Average Power Ratio (PAPR)
Peak-to-Average Power Ratio (PAPR) Wireless Information Transmission System Lab Institute of Communications Engineering National Sun Yat-sen University 2011/07/30 王森弘 Multi-carrier systems The complex
More informationBlock Processing Linear Equalizer for MIMO CDMA Downlinks in STTD Mode
Block Processing Linear Equalizer for MIMO CDMA Downlinks in STTD Mode Yan Li Yingxue Li Abstract In this study, an enhanced chip-level linear equalizer is proposed for multiple-input multiple-out (MIMO)
More informationFREQUENCY OFFSET ESTIMATION IN COHERENT OFDM SYSTEMS USING DIFFERENT FADING CHANNELS
FREQUENCY OFFSET ESTIMATION IN COHERENT OFDM SYSTEMS USING DIFFERENT FADING CHANNELS Haritha T. 1, S. SriGowri 2 and D. Elizabeth Rani 3 1 Department of ECE, JNT University Kakinada, Kanuru, Vijayawada,
More informationBEING wideband, chaotic signals are well suited for
680 IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II: EXPRESS BRIEFS, VOL. 51, NO. 12, DECEMBER 2004 Performance of Differential Chaos-Shift-Keying Digital Communication Systems Over a Multipath Fading Channel
More informationA New OFDM Transmission Scheme Using Orthogonal Code Multiplexing
A New OD Transmission Scheme Using Orthogonal Code ultiplexing Seong Keun Oh, Ki Seub Lee, and yung Hoon Sunwoo School of Electronics Engineering, Ajou University, San 5, Wonchon-Dong, Paldal-Gu, Suwon,
More informationComputationally Efficient Optimal Power Allocation Algorithms for Multicarrier Communication Systems
IEEE TRANSACTIONS ON COMMUNICATIONS, VOL. 48, NO. 1, 2000 23 Computationally Efficient Optimal Power Allocation Algorithms for Multicarrier Communication Systems Brian S. Krongold, Kannan Ramchandran,
More informationNoncoherent Demodulation for Cooperative Diversity in Wireless Systems
Noncoherent Demodulation for Cooperative Diversity in Wireless Systems Deqiang Chen and J. Nicholas Laneman Department of Electrical Engineering University of Notre Dame Notre Dame IN 46556 Email: {dchen
More informationOn Using Channel Prediction in Adaptive Beamforming Systems
On Using Channel rediction in Adaptive Beamforming Systems T. R. Ramya and Srikrishna Bhashyam Department of Electrical Engineering, Indian Institute of Technology Madras, Chennai - 600 036, India. Email:
More informationDetection and Estimation of Signals in Noise. Dr. Robert Schober Department of Electrical and Computer Engineering University of British Columbia
Detection and Estimation of Signals in Noise Dr. Robert Schober Department of Electrical and Computer Engineering University of British Columbia Vancouver, August 24, 2010 2 Contents 1 Basic Elements
More informationIN RECENT years, wireless multiple-input multiple-output
1936 IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, VOL. 3, NO. 6, NOVEMBER 2004 On Strategies of Multiuser MIMO Transmit Signal Processing Ruly Lai-U Choi, Michel T. Ivrlač, Ross D. Murch, and Wolfgang
More informationORTHOGONAL frequency division multiplexing (OFDM)
IEEE TRANSACTIONS ON BROADCASTING, VOL. 50, NO. 3, SEPTEMBER 2004 335 Modified Selected Mapping Technique for PAPR Reduction of Coded OFDM Signal Seung Hee Han, Student Member, IEEE, and Jae Hong Lee,
More informationSNR Estimation in Nakagami-m Fading With Diversity Combining and Its Application to Turbo Decoding
IEEE TRANSACTIONS ON COMMUNICATIONS, VOL. 50, NO. 11, NOVEMBER 2002 1719 SNR Estimation in Nakagami-m Fading With Diversity Combining Its Application to Turbo Decoding A. Ramesh, A. Chockalingam, Laurence
More informationEELE 6333: Wireless Commuications
EELE 6333: Wireless Commuications Chapter # 4 : Capacity of Wireless Channels Spring, 2012/2013 EELE 6333: Wireless Commuications - Ch.4 Dr. Musbah Shaat 1 / 18 Outline 1 Capacity in AWGN 2 Capacity of
More informationINTERSYMBOL interference (ISI) is a significant obstacle
IEEE TRANSACTIONS ON COMMUNICATIONS, VOL. 53, NO. 1, JANUARY 2005 5 Tomlinson Harashima Precoding With Partial Channel Knowledge Athanasios P. Liavas, Member, IEEE Abstract We consider minimum mean-square
More information1. Introduction. 2. OFDM Primer
A Novel Frequency Domain Reciprocal Modulation Technique to Mitigate Multipath Effect for HF Channel *Kumaresh K, *Sree Divya S.P & **T. R Rammohan Central Research Laboratory Bharat Electronics Limited
More informationOptimal Power Allocation over Fading Channels with Stringent Delay Constraints
1 Optimal Power Allocation over Fading Channels with Stringent Delay Constraints Xiangheng Liu Andrea Goldsmith Dept. of Electrical Engineering, Stanford University Email: liuxh,andrea@wsl.stanford.edu
More informationAN EFFICIENT RESOURCE ALLOCATION FOR MULTIUSER MIMO-OFDM SYSTEMS WITH ZERO-FORCING BEAMFORMER
AN EFFICIENT RESOURCE ALLOCATION FOR MULTIUSER MIMO-OFDM SYSTEMS WITH ZERO-FORCING BEAMFORMER Young-il Shin Mobile Internet Development Dept. Infra Laboratory Korea Telecom Seoul, KOREA Tae-Sung Kang Dept.
More informationBit-Interleaved Coded Modulation: Low Complexity Decoding
Bit-Interleaved Coded Modulation: Low Complexity Decoding Enis Aay and Ender Ayanoglu Center for Pervasive Communications and Computing Department of Electrical Engineering and Computer Science The Henry
More informationError Probability of Different Modulation Schemes for OFDM based WLAN standard IEEE a
Error Probability of Different Modulation Schemes for OFDM based WLAN standard IEEE 802.11a Sanjeev Kumar Asst. Professor/ Electronics & Comm. Engg./ Amritsar college of Engg. & Technology, Amritsar, 143001,
More informationTRANSMIT diversity has emerged in the last decade as an
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, VOL. 3, NO. 5, SEPTEMBER 2004 1369 Performance of Alamouti Transmit Diversity Over Time-Varying Rayleigh-Fading Channels Antony Vielmon, Ye (Geoffrey) Li,
More informationDegrees of Freedom of Multi-hop MIMO Broadcast Networks with Delayed CSIT
Degrees of Freedom of Multi-hop MIMO Broadcast Networs with Delayed CSIT Zhao Wang, Ming Xiao, Chao Wang, and Miael Soglund arxiv:0.56v [cs.it] Oct 0 Abstract We study the sum degrees of freedom (DoF)
More informationSymbol Error Rate of Quadrature Subbranch Hybrid Selection/Maximal-Ratio Combining in Rayleigh Fading Under Employment of Generalized Detector
Symbol Error Rate of Quadrature Subbranch Hybrid Selection/Maximal-Ratio Combining in Rayleigh Fading Under Employment of Generalized Detector VYACHESLAV TUZLUKOV School of Electrical Engineering and Computer
More informationSpring 2017 MIMO Communication Systems Solution of Homework Assignment #5
Spring 217 MIMO Communication Systems Solution of Homework Assignment #5 Problem 1 (2 points Consider a channel with impulse response h(t α δ(t + α 1 δ(t T 1 + α 3 δ(t T 2. Assume that T 1 1 µsecs and
More informationAn Efficient Subcarrier and Power Allocation Scheme for Multiuser MIMO-OFDM System
International Journal of Recent Development in Engineering and Technology Website: www.ijrdet.com (ISSN - (Online)) Volume, Issue, March ) An Efficient Subcarrier and Power Allocation Scheme for Multiuser
More informationUNEQUAL POWER ALLOCATION FOR JPEG TRANSMISSION OVER MIMO SYSTEMS. Muhammad F. Sabir, Robert W. Heath Jr. and Alan C. Bovik
UNEQUAL POWER ALLOCATION FOR JPEG TRANSMISSION OVER MIMO SYSTEMS Muhammad F. Sabir, Robert W. Heath Jr. and Alan C. Bovik Department of Electrical and Computer Engineering, The University of Texas at Austin,
More informationADAPTIVE RESOURCE ALLOCATION FOR WIRELESS MULTICAST MIMO-OFDM SYSTEMS
ADAPTIVE RESOURCE ALLOCATION FOR WIRELESS MULTICAST MIMO-OFDM SYSTEMS SHANMUGAVEL G 1, PRELLY K.E 2 1,2 Department of ECE, DMI College of Engineering, Chennai. Email: shangvcs.in@gmail.com, prellyke@gmail.com
More informationIJESRT. Scientific Journal Impact Factor: (ISRA), Impact Factor: 2.114
IJESRT INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY PERFORMANCE IMPROVEMENT OF CONVOLUTION CODED OFDM SYSTEM WITH TRANSMITTER DIVERSITY SCHEME Amol Kumbhare *, DR Rajesh Bodade *
More informationPerformance analysis of MISO-OFDM & MIMO-OFDM Systems
Performance analysis of MISO-OFDM & MIMO-OFDM Systems Kavitha K V N #1, Abhishek Jaiswal *2, Sibaram Khara #3 1-2 School of Electronics Engineering, VIT University Vellore, Tamil Nadu, India 3 Galgotias
More informationPerformance of Selected Diversity Techniques Over The α-µ Fading Channels
Performance of Selected Diversity Techniques Over The α-µ Fading Channels TAIMOUR ALDALGAMOUNI 1, AMER M. MAGABLEH, AHMAD AL-HUBAISHI Electrical Engineering Department Jordan University of Science and
More informationENERGY EFFICIENT WATER-FILLING ALGORITHM FOR MIMO- OFDMA CELLULAR SYSTEM
ENERGY EFFICIENT WATER-FILLING ALGORITHM FOR MIMO- OFDMA CELLULAR SYSTEM Hailu Belay Kassa, Dereje H.Mariam Addis Ababa University, Ethiopia Farzad Moazzami, Yacob Astatke Morgan State University Baltimore,
More informationPower Reduction in OFDM systems using Tone Reservation with Customized Convex Optimization
Power Reduction in OFDM systems using Tone Reservation with Customized Convex Optimization NANDALAL.V, KIRUTHIKA.V Electronics and Communication Engineering Anna University Sri Krishna College of Engineering
More informationIEEE TRANSACTIONS ON COMMUNICATIONS, VOL. 50, NO. 12, DECEMBER
IEEE TRANSACTIONS ON COMMUNICATIONS, VOL. 50, NO. 12, DECEMBER 2002 1865 Transactions Letters Fast Initialization of Nyquist Echo Cancelers Using Circular Convolution Technique Minho Cheong, Student Member,
More informationTHE EFFECT of multipath fading in wireless systems can
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, VOL. 47, NO. 1, FEBRUARY 1998 119 The Diversity Gain of Transmit Diversity in Wireless Systems with Rayleigh Fading Jack H. Winters, Fellow, IEEE Abstract In
More informationA New Adaptive Channel Estimation for Frequency Selective Time Varying Fading OFDM Channels
A New Adaptive Channel Estimation for Frequency Selective Time Varying Fading OFDM Channels Wessam M. Afifi, Hassan M. Elkamchouchi Abstract In this paper a new algorithm for adaptive dynamic channel estimation
More informationPower back-off for multiple target bit rates. Authors: Frank Sjöberg, Rickard Nilsson, Sarah Kate Wilson, Daniel Bengtsson, Mikael Isaksson
T1E1.4/98-371 1(8) Standards Project: T1E1.4 VDSL Title : Power bac-off for multiple target bit rates Source : Telia Research AB Contact: Göran Övist Telia Research AB, Aurorum 6, SE-977 75 Luleå, Sweden
More informationELEC E7210: Communication Theory. Lecture 11: MIMO Systems and Space-time Communications
ELEC E7210: Communication Theory Lecture 11: MIMO Systems and Space-time Communications Overview of the last lecture MIMO systems -parallel decomposition; - beamforming; - MIMO channel capacity MIMO Key
More informationNew Cross-layer QoS-based Scheduling Algorithm in LTE System
New Cross-layer QoS-based Scheduling Algorithm in LTE System MOHAMED A. ABD EL- MOHAMED S. EL- MOHSEN M. TATAWY GAWAD MAHALLAWY Network Planning Dep. Network Planning Dep. Comm. & Electronics Dep. National
More informationCombined Phase Compensation and Power Allocation Scheme for OFDM Systems
Combined Phase Compensation and Power Allocation Scheme for OFDM Systems Wladimir Bocquet France Telecom R&D Tokyo 3--3 Shinjuku, 60-0022 Tokyo, Japan Email: bocquet@francetelecom.co.jp Kazunori Hayashi
More informationAN EFFICIENT LINK PERFOMANCE ESTIMATION TECHNIQUE FOR MIMO-OFDM SYSTEMS
AN EFFICIENT LINK PERFOMANCE ESTIMATION TECHNIQUE FOR MIMO-OFDM SYSTEMS 1 K. A. Narayana Reddy, 2 G. Madhavi Latha, 3 P.V.Ramana 1 4 th sem, M.Tech (Digital Electronics and Communication Systems), Sree
More informationFrequency and Power Allocation for Low Complexity Energy Efficient OFDMA Systems with Proportional Rate Constraints
Frequency and Power Allocation for Low Complexity Energy Efficient OFDMA Systems with Proportional Rate Constraints Pranoti M. Maske PG Department M. B. E. Society s College of Engineering Ambajogai Ambajogai,
More informationENHANCED BANDWIDTH EFFICIENCY IN WIRELESS OFDMA SYSTEMS THROUGH ADAPTIVE SLOT ALLOCATION ALGORITHM
ENHANCED BANDWIDTH EFFICIENCY IN WIRELESS OFDMA SYSTEMS THROUGH ADAPTIVE SLOT ALLOCATION ALGORITHM K.V. N. Kavitha 1, Siripurapu Venkatesh Babu 1 and N. Senthil Nathan 2 1 School of Electronics Engineering,
More informationAn Energy-Division Multiple Access Scheme
An Energy-Division Multiple Access Scheme P Salvo Rossi DIS, Università di Napoli Federico II Napoli, Italy salvoros@uninait D Mattera DIET, Università di Napoli Federico II Napoli, Italy mattera@uninait
More informationImplementation and Comparative analysis of Orthogonal Frequency Division Multiplexing (OFDM) Signaling Rashmi Choudhary
Implementation and Comparative analysis of Orthogonal Frequency Division Multiplexing (OFDM) Signaling Rashmi Choudhary M.Tech Scholar, ECE Department,SKIT, Jaipur, Abstract Orthogonal Frequency Division
More informationExact BER Analysis of an Arbitrary Square/ Rectangular QAM for MRC Diversity with ICE in Nonidentical Rayleigh Fading Channels
Exact BER Analysis of an Arbitrary Square/ Rectangular QAM for MRC Diversity with ICE in Nonidentical Rayleigh Fading Channels aleh Najafizadeh School of Electrical and Computer Engineering Georgia Institute
More informationPower Minimization for Multi-Cell OFDM Networks Using Distributed Non-cooperative Game Approach
Power Minimization for Multi-Cell OFDM Networks Using Distributed Non-cooperative Game Approach Zhu Han, Zhu Ji, and K. J. Ray Liu Electrical and Computer Engineering Department, University of Maryland,
More informationInternational Journal of Emerging Technologies in Computational and Applied Sciences(IJETCAS)
International Association of Scientific Innovation and Research (IASIR) (An Association Unifying the Sciences, Engineering, and Applied Research) International Journal of Emerging Technologies in Computational
More informationOrthogonal Frequency Division Multiplexing (OFDM) based Uplink Multiple Access Method over AWGN and Fading Channels
Orthogonal Frequency Division Multiplexing (OFDM) based Uplink Multiple Access Method over AWGN and Fading Channels Prashanth G S 1 1Department of ECE, JNNCE, Shivamogga ---------------------------------------------------------------------***----------------------------------------------------------------------
More informationBER PERFORMANCE AND OPTIMUM TRAINING STRATEGY FOR UNCODED SIMO AND ALAMOUTI SPACE-TIME BLOCK CODES WITH MMSE CHANNEL ESTIMATION
BER PERFORMANCE AND OPTIMUM TRAINING STRATEGY FOR UNCODED SIMO AND ALAMOUTI SPACE-TIME BLOC CODES WITH MMSE CHANNEL ESTIMATION Lennert Jacobs, Frederik Van Cauter, Frederik Simoens and Marc Moeneclaey
More informationOFDM AS AN ACCESS TECHNIQUE FOR NEXT GENERATION NETWORK
OFDM AS AN ACCESS TECHNIQUE FOR NEXT GENERATION NETWORK Akshita Abrol Department of Electronics & Communication, GCET, Jammu, J&K, India ABSTRACT With the rapid growth of digital wireless communication
More informationPerformance Analysis of Maximum Likelihood Detection in a MIMO Antenna System
IEEE TRANSACTIONS ON COMMUNICATIONS, VOL. 50, NO. 2, FEBRUARY 2002 187 Performance Analysis of Maximum Likelihood Detection in a MIMO Antenna System Xu Zhu Ross D. Murch, Senior Member, IEEE Abstract In
More informationProportional Fair Scheduling for Wireless Communication with Multiple Transmit and Receive Antennas 1
Proportional Fair Scheduling for Wireless Communication with Multiple Transmit and Receive Antennas Taewon Park, Oh-Soon Shin, and Kwang Bok (Ed) Lee School of Electrical Engineering and Computer Science
More informationLow Complexity Decoding of Bit-Interleaved Coded Modulation for M-ary QAM
Low Complexity Decoding of Bit-Interleaved Coded Modulation for M-ary QAM Enis Aay and Ender Ayanoglu Center for Pervasive Communications and Computing Department of Electrical Engineering and Computer
More informationTechnical University Berlin Telecommunication Networks Group
Technical University Berlin Telecommunication Networks Group Comparison of Different Fairness Approaches in OFDM-FDMA Systems James Gross, Holger Karl {gross,karl}@tkn.tu-berlin.de Berlin, March 2004 TKN
More informationLIMITED FEEDBACK POWER LOADING FOR OFDM
LIMITED FEEDBACK POWER LOADING FOR OFDM David J. Love School of Electrical and Computer Engineering Purdue University West Lafayette, IN 47907 djlove@ecn.purdue.edu and Robert W. Heath, Jr. Dept. of Electrical
More informationDiversity Techniques
Diversity Techniques Vasileios Papoutsis Wireless Telecommunication Laboratory Department of Electrical and Computer Engineering University of Patras Patras, Greece No.1 Outline Introduction Diversity
More informationAchieving Low Outage Probability with Network Coding in Wireless Multicarrier Multicast Systems
Achieving Low Outage Probability with Networ Coding in Wireless Multicarrier Multicast Systems Juan Liu, Wei Chen, Member, IEEE, Zhigang Cao, Senior Member, IEEE, Ying Jun (Angela) Zhang, Senior Member,
More informationORTHOGONAL frequency division multiplexing (OFDM)
144 IEEE TRANSACTIONS ON BROADCASTING, VOL. 51, NO. 1, MARCH 2005 Performance Analysis for OFDM-CDMA With Joint Frequency-Time Spreading Kan Zheng, Student Member, IEEE, Guoyan Zeng, and Wenbo Wang, Member,
More informationReduction of PAR and out-of-band egress. EIT 140, tom<at>eit.lth.se
Reduction of PAR and out-of-band egress EIT 140, tomeit.lth.se Multicarrier specific issues The following issues are specific for multicarrier systems and deserve special attention: Peak-to-average
More informationCOMBINING GALOIS WITH COMPLEX FIELD CODING FOR HIGH-RATE SPACE-TIME COMMUNICATIONS. Renqiu Wang, Zhengdao Wang, and Georgios B.
COMBINING GALOIS WITH COMPLEX FIELD CODING FOR HIGH-RATE SPACE-TIME COMMUNICATIONS Renqiu Wang, Zhengdao Wang, and Georgios B. Giannakis Dept. of ECE, Univ. of Minnesota, Minneapolis, MN 55455, USA e-mail:
More informationAdaptive Modulation for Transmitter Antenna Diversity Mobile Radio Systems 1
Adaptive Modulation for Transmitter Antenna Diversity Mobile Radio Systems Shengquan Hu +, Alexandra Duel-Hallen *, Hans Hallen^ + Spreadtrum Communications Corp. 47 Patrick Henry Dr. Building 4, Santa
More informationJoint Adaptive Modulation and Diversity Combining with Feedback Error Compensation
Joint Adaptive Modulation and Diversity Combining with Feedback Error Compensation Seyeong Choi, Mohamed-Slim Alouini, Khalid A. Qaraqe Dept. of Electrical Eng. Texas A&M University at Qatar Education
More informationMULTICARRIER code-division multiple access (MC-
2064 IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, VOL. 4, NO. 5, SEPTEMBER 2005 A Novel Prefiltering Technique for Downlink Transmissions in TDD MC-CDMA Systems Michele Morelli, Member, IEEE, and L. Sanguinetti
More informationPerformance Evaluation of MIMO-OFDM Systems under Various Channels
Performance Evaluation of MIMO-OFDM Systems under Various Channels C. Niloufer fathima, G. Hemalatha Department of Electronics and Communication Engineering, KSRM college of Engineering, Kadapa, Andhra
More informationReduced Complexity of QRD-M Detection Scheme in MIMO-OFDM Systems
Advanced Science and echnology Letters Vol. (ASP 06), pp.4- http://dx.doi.org/0.457/astl.06..4 Reduced Complexity of QRD-M Detection Scheme in MIMO-OFDM Systems Jong-Kwang Kim, Jae-yun Ro and young-kyu
More informationANALOGUE TRANSMISSION OVER FADING CHANNELS
J.P. Linnartz EECS 290i handouts Spring 1993 ANALOGUE TRANSMISSION OVER FADING CHANNELS Amplitude modulation Various methods exist to transmit a baseband message m(t) using an RF carrier signal c(t) =
More informationTHE ADAPTIVE CHANNEL ESTIMATION FOR STBC-OFDM SYSTEMS
ISANBUL UNIVERSIY JOURNAL OF ELECRICAL & ELECRONICS ENGINEERING YEAR VOLUME NUMBER : 2005 : 5 : 1 (1333-1340) HE ADAPIVE CHANNEL ESIMAION FOR SBC-OFDM SYSEMS Berna ÖZBEK 1 Reyat YILMAZ 2 1 İzmir Institute
More informationPerformance of Wideband Mobile Channel with Perfect Synchronism BPSK vs QPSK DS-CDMA
Performance of Wideband Mobile Channel with Perfect Synchronism BPSK vs QPSK DS-CDMA By Hamed D. AlSharari College of Engineering, Aljouf University, Sakaka, Aljouf 2014, Kingdom of Saudi Arabia, hamed_100@hotmail.com
More informationPerformance Analysis of the D-STTD Communication System with AMC Scheme
, 2009, 5, 325-329 doi:10.4236/ijcns.2009.25035 Published Online August 2009 (http://www.scirp.org/journal/ijcns/). Performance Analysis of the D-STTD Communication System with AMC Scheme Jeonghwan LEE
More informationComb type Pilot arrangement based Channel Estimation for Spatial Multiplexing MIMO-OFDM Systems
Comb type Pilot arrangement based Channel Estimation for Spatial Multiplexing MIMO-OFDM Systems Mr Umesha G B 1, Dr M N Shanmukha Swamy 2 1Research Scholar, Department of ECE, SJCE, Mysore, Karnataka State,
More informationAdaptive Resource Allocation in Wireless Relay Networks
Adaptive Resource Allocation in Wireless Relay Networks Tobias Renk Email: renk@int.uni-karlsruhe.de Dimitar Iankov Email: iankov@int.uni-karlsruhe.de Friedrich K. Jondral Email: fj@int.uni-karlsruhe.de
More informationPerformance Evaluation of Nonlinear Equalizer based on Multilayer Perceptron for OFDM Power- Line Communication
International Journal of Electrical Engineering. ISSN 974-2158 Volume 4, Number 8 (211), pp. 929-938 International Research Publication House http://www.irphouse.com Performance Evaluation of Nonlinear
More information